1. Field of the Invention
This invention relates to a digital signal encoding apparatus for encoding input digital signals.
2. Prior Art
As a technique of high efficiency encoding of input signals, there are known encoding techniques by so-called bit allocation, according to which input signals are divided into plural channels on the time or frequency axis and certain numbers of bits are adaptively allocated to the respective channels (bit allocation). Among the above mentioned encoding techniques by bit allocation are so-called sub-band coding (SBC) in which voice signals on the time axis are divided into signals of a plurality of frequency bands for encoding, a so-called adaptive transformation coding (ATC) in which voice signals on the time axis are transformed into signals on the frequency axis by orthogonal transformation and the resulting signals are divided into signals of a plurality of frequency bands for adaptive coding for each frequency band, and a so-called adaptive bit allocation (APC-AB) which is a combination of the above mentioned SBC and APC and in which the voice signals on the time axis are divided into signals of a plurality of frequency bands and the signals of the respective bands are converted into base band or low range signals, after which multiple order linear predictive analyses are performed for predictive coding.
The sub-band coding, for example, is performed by a circuit shown in FIG. 1. In this figure, digital voice signals, supplied to an input terminal 110 of an encoder 130, are fed to frequency division filters 131.sub.1 to 131.sub.n, which may for example be mirror filters, such as quadrature mirror filters (QMFs), so as to be limited in the frequency range and be shifted to lower frequency sides. That is, in these frequency division filters 131.sub.1 to 131.sub.n, the input digital voice signals are divided into separate frequency bands by band-pass filters or BPFs and subsequently passed through low-pass filters so as to be shifted to the lower frequency sides by amounts corresponding to the center frequencies of the pass bands of the LPFs. The signals from the filters are then supplied to quantizers 134.sub.1 to 134.sub.n, respectively, to undergo down-sampling at a suitable sampling frequency. It is noted that a higher sampling frequency should be used for a broader frequency band. The signals in which the data have been compressed by requantization in this manner are outputted at terminal 138 by way of a multiplexer 136. The output signals are then transmitted over a transmission channel to a terminal 148 of a decoder 140 and thence to dequantizers 144.sub.1 to 144.sub.n via demultiplexer 149 for decoding. The decoded signals are converted by frequency converters 142.sub.1 to 142.sub.n into signals of the frequency bands on the time axis and adds at a summing junction 146 so as to be outputted at a terminal 150 as the decoded voice signals.
In signal data compression by the encoder 130, quantization bits are adaptively allocated to the respective frequency bands for minimizing the effects of noises produced on data compression of voice signals to improve the quality. The decoder 140 also acquires the bit allocation information by some means or other in performing the decoding.
The conventional practice for acquiring the bit allocation information has been to transmit the energy value information of each frequency band as side information in addition to the signals of the respective bands. In this case, the energy values of signals of the respective bands are computed at energy detection means 133.sub.1 to 133.sub.n, from the signals divided into the frequency bands by the frequency division filters 131.sub.1 to 131.sub.n of the encoder 130 and, based on the computed values, the optimum numbers of bit allocation and the steps of quantization at the time of quantization of the signals of the respective bands are found at a allocation-step computing unit 135. The results obtained at the computing unit 135 are used for requantizing the signals of the respective bands at quantizers 134.sub.1 to 134.sub.n. The output signals, that is the auxiliary or side information from the allocation-step computing unit 135, are transmitted to an allocation-step computing unit 145 of the decoder 140, and the data from the unit 145 are transmitted to dequantizers 144.sub.1 to 144.sub.n, where an inverse operation of that performed at the quantizers 134.sub.1 to 134.sub.n is performed to perform signal decoding.
With the above described frequency division and coding, noise shaping or the like may be taken into account in keeping with human auditory characteristics, and more information may be allocated to those frequency bands in which the voice energies are concentrated or which contribute more to the subjective voice quality, such as clarity. Signal quantization and dequantization for the respective frequency bands are performed with the allocated number of bits for reducing the extent of obstruction of hearing by the quantization noises to reduce the number of bits on the whole. The above mentioned frequency division and coding results in generation of quantization noises only in the frequency band concerned without affecting the remaining bands. Meanwhile, when the energy value information is transmitted as the auxiliary data, as described above, the energy values of the signals of the respective bands may advantageously be employed as the quantization step widths or normalization factors of the respective frequency band signals.
Should the frequency division and coding be applied to musical or voice signals, the frequency band division is usually performed in such a manner that, in order to suit to the frequency analysis capability of the human auditory sense, a narrower bandwidth and a broader bandwidth are selected for the low frequency range and the high frequency range, respectively.
However, with such a frequency band division, suited to the frequency analysis capability of the human auditory sense, if the definition of temporal analyses for the respective frequency bands, that is the time width as the unit of analyses along the time axis, should be the same, the size of the analytic block for each frequency range, that is the number of samples or data, will differ from one frequency range to another because of the difference in the band widths of the frequency bands, with the result that the efficiency of the analytic processing and hence the encoding efficiency are lowered. On the other hand, the constant amplitude period is thought to be longer and shorter for the low and high frequency signals, respectively, so that an efficient encoding consistent with the constant amplitude period cannot be performed.